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---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: convnextv2-tiny-1k-224-finetuned-two-four
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# convnextv2-tiny-1k-224-finetuned-two-four
This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5662
- Accuracy: 0.7352
- F1: 0.7327
- Precision: 0.7370
- Recall: 0.7352
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6983 | 0.9655 | 14 | 0.6720 | 0.5974 | 0.5694 | 0.6054 | 0.5974 |
| 0.6804 | 2.0 | 29 | 0.6609 | 0.6324 | 0.6190 | 0.6374 | 0.6324 |
| 0.6796 | 2.9655 | 43 | 0.6634 | 0.6083 | 0.6084 | 0.6084 | 0.6083 |
| 0.6886 | 4.0 | 58 | 0.6547 | 0.6171 | 0.6104 | 0.6161 | 0.6171 |
| 0.6577 | 4.9655 | 72 | 0.6577 | 0.6127 | 0.5724 | 0.6407 | 0.6127 |
| 0.6439 | 6.0 | 87 | 0.6196 | 0.6477 | 0.6339 | 0.6559 | 0.6477 |
| 0.602 | 6.9655 | 101 | 0.6125 | 0.6652 | 0.6585 | 0.6986 | 0.6652 |
| 0.5974 | 8.0 | 116 | 0.6224 | 0.6696 | 0.6601 | 0.7141 | 0.6696 |
| 0.5841 | 8.9655 | 130 | 0.5800 | 0.7002 | 0.7005 | 0.7011 | 0.7002 |
| 0.581 | 10.0 | 145 | 0.5822 | 0.7265 | 0.7262 | 0.7262 | 0.7265 |
| 0.5716 | 10.9655 | 159 | 0.5812 | 0.7068 | 0.7035 | 0.7083 | 0.7068 |
| 0.5611 | 12.0 | 174 | 0.5778 | 0.7221 | 0.7150 | 0.7319 | 0.7221 |
| 0.5411 | 12.9655 | 188 | 0.5652 | 0.7352 | 0.7341 | 0.7351 | 0.7352 |
| 0.5361 | 14.0 | 203 | 0.5670 | 0.7374 | 0.7347 | 0.7395 | 0.7374 |
| 0.5416 | 14.4828 | 210 | 0.5662 | 0.7352 | 0.7327 | 0.7370 | 0.7352 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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